CVE-2026-24160
Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.
NVD · uneditedNVIDIA TRT-LLM for any platform contains a vulnerability where an attacker could cause an unchecked return value to a null pointer dereference. A successful exploit of this vulnerability might lead to denial of service.
Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.
dbcve analysis · moderate confidenceNVIDIA TRT-LLM contains an unchecked return value vulnerability that leads to null pointer dereference. An attacker can trigger this condition by providing specific input that causes a function to return an unexpected value, which is then used without validation, resulting in a null dereference and denial of service.
Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.
Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.
NVD · CPE data< 1.2CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.
From the vector- Attack vector
- Network
- Complexity
- Low
- Privileges
- None
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- None
- Integrity
- None
- Availability
- High
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.
dbcve checksWork through these to decide whether this CVE applies to you.
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Identify if NVIDIA TRT-LLM is installedCheck for the presence of TensorRT-LLM libraries or packages in your environment. Common locations include /usr/local/trt-llm, /opt/nvidia/trt-llm, or via package managers like pip (pip list | grep tensorrt_llm).Affected if TensorRT-LLM is present in the system
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Determine the installed TensorRT-LLM versionRun the version check command for your installation method. For pip: pip show tensorrt-llm or import tensorrt_llm; print(tensorrt_llm.__version__). For containerized setups: check the image tag or label.Affected if The version cannot be determined or is below 1.2
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Verify the version is within affected rangeCompare your installed version against the affected range: versions < 1.2 are vulnerable.Affected if Installed version is less than 1.2
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Assess input exposure to the vulnerable code pathDetermine if the system processes untrusted or crafted inputs through TensorRT-LLM APIs, particularly any custom plugins, inference endpoints, or batch processing workflows that interact with the unchecked return value code path.Affected if Untrusted or specially crafted inputs can be passed to TensorRT-LLM APIs
The environment is affected if TensorRT-LLM is installed with a version less than 1.2 and processes inputs that could trigger the null pointer dereference condition.
Generated from the published advisory. Verify against your own configuration.
Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.
dbcve · scoped1.2
Apply the NVIDIA patch or update to TRT-LLM once released. Until then, restrict access to TRT-LLM interfaces to trusted users only to reduce attack surface.
TensorRT LLM version 1.2
- Identify the current TensorRT LLM version installed in your environment using the NVIDIA container or package manager
- Upgrade TensorRT LLM to version 1.2 or later by pulling the updated NVIDIA container or reinstalling the package
- Verify the upgrade was successful by checking the installed TensorRT LLM version matches 1.2 or higher
- Test that your workloads run normally after the upgrade to confirm the null pointer dereference issue is resolved
Generated from the published advisory — verify against the referenced sources before acting.
- Consultation4.0 h
- Implementation8.0 h
- Testing6.0 h
- Review / QA2.0 h
An estimate, not a bill — we confirm scope with you before any work starts. Need it this week? Rush from $5,600.
Scan for this in your stack
Free · runs locallyCheck whether your project pulls in CVE-2026-24160 — or any other known-vulnerable package — straight from your lock files. Free and open source; it runs locally and uploads nothing.
References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.
Primary sourcesPractitioner notes
ContributedPeer-ranked notes from engineers who’ve handled CVE-2026-24160 in production — separate from our analysis above.
The advisory tells you what broke. It rarely tells you what actually worked. If you’ve dealt with this one, that detail is what the next engineer is searching for.
- The version that genuinely resolved it — not the one the vendor claimed
- A config change or rule that shut the vector down
- A gotcha in the upgrade path that cost you an afternoon
No notes yet
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A place for practitioners to share what actually worked: a mitigation you’ve tested, a configuration change, a version- or environment-specific caveat, or a link to a verified patch. The most useful notes rise to the top as peers upvote them, so the signal stays high.
- Verified mitigations, workarounds, and config changes
- Version or environment caveats, and links to real fixes
- No weaponised exploit code, or anything meant to cause harm
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